7.1. DataLad extensions¶
DataLad’s commands cover a broad range of domain-agnostic use cases. However, there are extension packages that can add specialized functionality with additional commands. Table 7.1 lists a number of such extensions.
DataLad extensions are shipped as separate Python packages, and are not included in DataLad itself. Instead, users needing a particular extension can install the extension package – either on top of DataLad, if already installed, or on its own. In the latter case, the extension will then pull in DataLad core automatically, with no need to first or simultaneously install DataLad itself explicitly. The installation is done with standard Python package managers, such as pip, and beyond installation of the package, no additional setup is required.
DataLad extensions listed here are of various maturity levels. Check out their documentation and the sections or chapters associated with an extension to find out more about them.
Name |
Description |
---|---|
Equips DataLad’s |
|
One of the initial goals behind DataLad was to provide access
to already existing data resources. With
|
|
Equips DataLad with an alternative command suite and advanced tooling for metadata handling (extraction, aggregation, reporting). |
|
Metadata extraction support for a range of standards common to neuroimaging data. The usecase An automatically and computationally reproducible neuroimaging analysis from scratch demonstrates how this extension can be used. |
|
Enables DataLad to interface and work with the Open Science Framework. Use it to publish your dataset’s data to an OSF project, thus utilizing the OSF for dataset storage and sharing. |
|
Equips DataLad with a set of commands to obtain and monitor imaging data releases of the UKBiobank. An introduction can be found in chapter |
|
Equips DataLad with a set of commands to track XNAT projects. An alternative, more basic method to retrieve data from an XNAT server is outlined in section Configure custom data access. |
To install a DataLad extension, use
$ pip install <extension-name>
such as in
$ pip install datalad-container
Afterwards, the new DataLad functionality the extension provides is readily available.
Some extensions could also be available from the software distribution (e.g., NeuroDebian or conda) you used to install DataLad itself. Visit the datalad-extensions project to review available versions and their status.